Building Enterprise-Grade Big Data Apps with Low-Code Platforms


Big Data

Low-code platforms are game-changing digital platforms that help organizations fast-track their digital transformation journey. A low-code refers to a visual approach to the development of software and applications. It enables the extraction and automation of every step of the application lifecycle to enable rapid delivery of a variety of software solutions. According to Gartner, low-code platforms will drive 65% of all app development functions by 2024, while nearly 66% of big companies will use at least four low-code platforms in their business environment.

Low-code platforms provide distinct capabilities around the software development lifecycle from planning applications through deployment and monitoring. They may also interface with automated testing and DevOps platforms.


Why Low-Code Platforms?

By using low-code development platforms, companies can create applications in a matter of time, with the resources they have. The platforms offer various hosting options, including proprietary managed clouds, public cloud hosting options, and data center deployments. Some low-code platforms can be used as code generators, while others generate models.

Low-code platforms also enable different development paradigms. They are a constructive tool for developers, enabling rapid development, integration, and automation.

So, what basically a low-code platform can do for businesses? The answer is it can fasten development process time, lessen development costs, enable easy integration, provide enhanced security, automate operational processes as required, reduce workloads from IT departments, and much more.


Building Big Data Apps Using Low Code

Today, the demand for developers to support multiple projects as new languages, processes, and applications are implemented is on the rise. However, the use of low-code platforms will enable non-tech professionals to develop applications at scale. Simultaneously, this will let experts free from routine work.

Low-code platforms can support data science initiatives by allowing developers to build data visualizations. As a low-code platform has the potential to automate analysis patterns into libraries, it makes it easier for developers to embed analytical components. Leveraging traditional development approaches for building big data applications can significantly impede developers’ bandwidth and go-to-market time of the application. That is why most analytics companies are using a low code approach to build smarter machine learning solutions and services.

Building big data apps using low-code platforms delivers considerable benefits.

Improved Business Agility: Low-code platforms allow citizen developers to build applications in a fraction of time. As it removes workload pressure from professional developers and enables them to focus on other code-intensive tasks, it improves business agility.

Fasten Development and Deployment Process Time: A low-code platform can dramatically enhance the software development process and lower the go-to-market time by 50 percent. The platforms leverage built-in apps, pre-built components, and templates, microservices and open-source libraries that help shorten the development process time.

Anyone can Develop Software: A low-code platform allows anyone in an organization to collaborate to deliver the best solutions, unleashing the creative potential of business teams and IT users. They can build apps without any requirement of coding and other technical knowledge and background.

Comprehensively, a low-code platform to build big data applications provides an easy and user-friendly environment from the development to deployment of applications.

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